Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by ...
Quantum cryptography has emerged as a radical research field aimed at mitigating various security threats in modern communication systems. The integration of Quantum Machine Learning (QML) protocols ...
Traffic signs are pivotal components of traffic management, ensuring the regulation and safety of road traffic. However, existing detection methods often suffer from low accuracy and poor real-time ...
Abstract: The advancement of intelligent transportation systems is crucial for improving road safety and optimizing traffic flow. In this paper, we present SafeSmartDrive, an integrated transportation ...
LUCID (Lightweight, Usable CNN in DDoS Detection) is a lightweight Deep Learning-based DDoS detection framework suitable for online resource-constrained environments, which leverages Convolutional ...
Convolutional neural networks (CNN) have enabled significant improvements in pedestrian detection owing to the strong representation ability of the CNN features. However, it is generally difficult to ...
Accurate and Reliable Detection of Traffic Lights Using Multiclass Learning and Multiobject Tracking
Abstract: Automatic detection of traffic lights has great importance to road safety. This paper presents a novel approach that combines computer vision and machine learning techniques for accurate ...
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